vit-base-patch16-224-in21k-eurosat
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3394
- Accuracy: 0.9802
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7076 | 0.98 | 33 | 0.6119 | 0.9696 |
| 0.4469 | 1.98 | 66 | 0.4190 | 0.9788 |
| 0.3497 | 2.98 | 99 | 0.3555 | 0.9788 |
| 0.3048 | 3.98 | 132 | 0.3394 | 0.9802 |
| 0.2983 | 4.98 | 165 | 0.3394 | 0.9802 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2